الفهرس 
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Abstract
Cloud computing architecture has some issues with real-time applications and internet of things (IoT) devices. As cloud computing is a centralized network and the location of the data center is very far from the end-user devices, cloud computing cannot support the real¬time application with good efficiency. The IoT devices are usually generating a huge amount of data that needs to be collected and processed in a few seconds. Besides that, the devices usually are smart devices with very limited storage and computation capabilities.
The physical location of the cloud data center is very far from the end-user, which delays the response of the cloud for the end-user request. As a result, we are going to use the fog computing network for applications that need an immediate response. The fog nodes are very close to the end-user, which makes the responses for the computing and storage requests are very reliable to real-time applications.
Fog computing uses near-user edge devices that are usually smart devices with very limited storage and computation resources; hence, the authentication process should be lightweight to be suitable for fog computing environment. To cope with these challenges, we propose a Lightweight Anonymous Mutual Authentication Scheme (LAMAS) for securing fog computing is proposed based on elliptic curve cryptography), few hash functions, XOR operations, and symmetric encryption/decryption. The proposed scheme succeeds to achieve mutual authentication between fog users and the fog servers even if the fog server is added after user registration, without need to re-register or do any more computation. Additionally, the fog user’s identity is totally hidden and cannot be predicted due to the Elliptic Curve Discrete Logarithm Problem (ECDLP). Moreover, formal and
informal security analysis is conducted to prove the security of the proposed scheme. Furthermore, comparisons with related schemes are carried out to demonstrate the superiority and efficiency of the proposed scheme in terms of computation cost and storage requirements.